# Load Data
source(here('scripts', 'Other_Functions.R'))
data <- load_processed_data_all_conditions()
data_long <- load_processed_data_all_conditions_long()
data_long$Condition_num <- as.numeric(data_long$Condition)
# Figure Parameters
source(here('scripts', 'Figure_Parameters.R'))
# Data manipulation
data_long$Reliability_factor <- as.factor(data_long$Reliability)
data_long$Block_factor <- as.factor(data_long$Block)
# Subsets
data_long_50 <- data_long %>%
filter(Condition == '50% Decreasing' | Condition == '50% Increasing')
# remove the other possible factors
data_long_50$Condition <- factor(data_long_50$Condition, levels = c('50% Decreasing', '50% Increasing'))
# repalce with 1 or 2
data_long_50$Condition_num <- as.numeric(data_long_50$Condition)
data_long_70 <- data_long %>%
filter(Condition == '70% Decreasing' | Condition == '70% Increasing')
# remove the other possible factors
data_long_70$Condition <- factor(data_long_70$Condition, levels = c('70% Decreasing', '70% Increasing'))
# repalce with 1 or 2
data_long_70$Condition_num <- as.numeric(data_long_70$Condition)
# ggplot histogram of trust
g1 <- ggplot(data_long, aes(x=Trust)) +
geom_histogram(position = "dodge", bins = 100) +
theme_classic() +
labs(title = "Trust", x = "Trust", y = "Frequency")
print(g1)
# ggplot histogram of confidence
g2 <- ggplot(data_long, aes(x=Confidence)) +
geom_histogram(position = "dodge", bins = 100) +
theme_classic() +
labs(title = "Confidence", x = "Confidence", y = "Frequency")
print(g2)
# ggplot histogram of reliance
g3 <- ggplot(data_long, aes(x=Reliance)) +
geom_histogram(position = "dodge", bins = 100) +
theme_classic() +
labs(title = "Reliance", x = "Reliance", y = "Frequency")
print(g3)
# Show Correlations
cor <- cor(data_long[,c("Trust", "Reliability", "Confidence", "Reliance", "Condition_num", "Performance_Before", "Performance_After")])
corrplot(cor, method = "circle")
# Assumptions
# Normality
qqnorm(data_long$Trust)
qqline(data_long$Trust)
qqnorm(data_long$Confidence)
qqline(data_long$Confidence)
qqnorm(data_long$Reliance)
qqline(data_long$Reliance)
# Homoscedasticity
plot(data_long$Trust ~ data_long$Reliability)
plot(data_long$Trust ~ data_long$Confidence)
plot(data_long$Trust ~ data_long$Reliance)
plot(data_long$Trust ~ data_long$Performance_After)
plot(data_long$Reliance ~ data_long$Reliability)
plot(data_long$Reliance ~ data_long$Confidence)
plot(data_long$Reliance ~ data_long$Performance_After)
plot(data_long$Confidence ~ data_long$Reliability)
plot(data_long$Confidence ~ data_long$Performance_After)
plot(data_long$Performance_After ~ data_long$Reliability)
# Sphericity
shapiro.test(data_long$Trust)
##
## Shapiro-Wilk normality test
##
## data: data_long$Trust
## W = 0.96534, p-value = 2.168e-14
shapiro.test(data_long$Confidence)
##
## Shapiro-Wilk normality test
##
## data: data_long$Confidence
## W = 0.93476, p-value < 2.2e-16
shapiro.test(data_long$Reliance)
##
## Shapiro-Wilk normality test
##
## data: data_long$Reliance
## W = 0.87745, p-value < 2.2e-16
shapiro.test(data_long$Performance_Before)
##
## Shapiro-Wilk normality test
##
## data: data_long$Performance_Before
## W = 0.98875, p-value = 9.285e-07
shapiro.test(data_long$Performance_After)
##
## Shapiro-Wilk normality test
##
## data: data_long$Performance_After
## W = 0.96795, p-value = 9.419e-14
# Everything Model
m50_1 <- lmer(data = data_long_50, Trust ~ Condition * Reliability * Confidence * Reliance * (1 | Participant))
## Warning: Some predictor variables are on very different scales: consider
## rescaling
summary(m50_1)
## Linear mixed model fit by REML ['lmerMod']
## Formula: Trust ~ Condition * Reliability * Confidence * Reliance * (1 |
## Participant)
## Data: data_long_50
##
## REML criterion at convergence: 3036.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.8792 -0.4320 -0.0012 0.4522 3.0305
##
## Random effects:
## Groups Name Variance Std.Dev.
## Participant (Intercept) 74.17 8.612
## Residual 17.11 4.136
## Number of obs: 480, groups: Participant, 80
##
## Fixed effects:
## Estimate Std. Error
## (Intercept) 46.276500 13.572137
## Condition50% Increasing -16.186487 19.277093
## Reliability -0.064241 0.183336
## Confidence 0.356908 0.153062
## Reliance -52.982108 35.367254
## Condition50% Increasing:Reliability 0.140755 0.235453
## Condition50% Increasing:Confidence 0.206110 0.220458
## Reliability:Confidence 0.001160 0.002079
## Condition50% Increasing:Reliance 92.633649 45.660402
## Reliability:Reliance 0.649169 0.437598
## Confidence:Reliance 0.635282 0.404977
## Condition50% Increasing:Reliability:Confidence -0.001624 0.002706
## Condition50% Increasing:Reliability:Reliance -1.095827 0.552562
## Condition50% Increasing:Confidence:Reliance -0.995395 0.523430
## Reliability:Confidence:Reliance -0.007611 0.005002
## Condition50% Increasing:Reliability:Confidence:Reliance 0.011775 0.006329
## t value
## (Intercept) 3.410
## Condition50% Increasing -0.840
## Reliability -0.350
## Confidence 2.332
## Reliance -1.498
## Condition50% Increasing:Reliability 0.598
## Condition50% Increasing:Confidence 0.935
## Reliability:Confidence 0.558
## Condition50% Increasing:Reliance 2.029
## Reliability:Reliance 1.483
## Confidence:Reliance 1.569
## Condition50% Increasing:Reliability:Confidence -0.600
## Condition50% Increasing:Reliability:Reliance -1.983
## Condition50% Increasing:Confidence:Reliance -1.902
## Reliability:Confidence:Reliance -1.522
## Condition50% Increasing:Reliability:Confidence:Reliance 1.861
##
## Correlation matrix not shown by default, as p = 16 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling
tab_model(m50_1)
| Â | Trust | ||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 46.28 | 19.61 – 72.95 | 0.001 |
|
Condition [50% Increasing] |
-16.19 | -54.07 – 21.70 | 0.402 |
| Reliability | -0.06 | -0.42 – 0.30 | 0.726 |
| Confidence | 0.36 | 0.06 – 0.66 | 0.020 |
| Reliance | -52.98 | -122.48 – 16.52 | 0.135 |
|
Condition [50% Increasing] × Reliability |
0.14 | -0.32 – 0.60 | 0.550 |
|
Condition [50% Increasing] × Confidence |
0.21 | -0.23 – 0.64 | 0.350 |
| Reliability × Confidence | 0.00 | -0.00 – 0.01 | 0.577 |
|
Condition [50% Increasing] × Reliance |
92.63 | 2.91 – 182.36 | 0.043 |
| Reliability × Reliance | 0.65 | -0.21 – 1.51 | 0.139 |
| Confidence × Reliance | 0.64 | -0.16 – 1.43 | 0.117 |
|
(Condition [50% Increasing] × Reliability) × Confidence |
-0.00 | -0.01 – 0.00 | 0.549 |
|
(Condition [50% Increasing] × Reliability) × Reliance |
-1.10 | -2.18 – -0.01 | 0.048 |
|
(Condition [50% Increasing] × Confidence) × Reliance |
-1.00 | -2.02 – 0.03 | 0.058 |
|
(Reliability × Confidence) × Reliance |
-0.01 | -0.02 – 0.00 | 0.129 |
|
(Condition [50% Increasing] × Reliability × Confidence) × Reliance |
0.01 | -0.00 – 0.02 | 0.063 |
| Random Effects | |||
| σ2 | 17.11 | ||
| τ00 Participant | 74.17 | ||
| ICC | 0.81 | ||
| N Participant | 80 | ||
| Observations | 480 | ||
| Marginal R2 / Conditional R2 | 0.301 / 0.869 | ||
# Visualize Trust by Confidence
g1 <- ggplot(data_long_50, aes(x=Confidence, y=Trust)) +
geom_smooth(alpha = 0.5, method = 'lm') +
geom_point() +
theme_classic() +
labs(title = "Trust by Confidence", x = "Confidence", y = "Trust") +
theme(plot.title = element_text(size=title_size)) +
xlim(0, 100) +
ylim(0, 100)
print(g1)
## `geom_smooth()` using formula = 'y ~ x'
# Visualize Interactions (Condition, Reliance)
g2 <- ggplot(data_long_50, aes(x=Reliance, y=Trust, color=Condition)) +
geom_smooth(alpha = 0.5, method = 'lm') +
geom_point() +
theme_classic() +
labs(title = "Trust by Reliance by Condition", x = "Reliance", y = "Trust") +
theme(plot.title = element_text(size=title_size)) +
xlim(0, 1) +
ylim(0, 100)
print(g2)
## `geom_smooth()` using formula = 'y ~ x'
# Visualize Interactions (Condition, Reliability, Reliance)
g3 <- ggplot(data_long_50, aes(x=Reliance, y=Trust, color=Reliability_factor, group=Reliability_factor)) +
geom_smooth(alpha = 0.1, method = 'lm') +
geom_point() +
theme_classic() +
labs(title = "Trust by Reliance by Reliability", x = "Reliance", y = "Trust") +
theme(plot.title = element_text(size=title_size)) +
facet_wrap(~Condition) +
xlim(0, 1) +
ylim(0, 100)
print(g3)
## `geom_smooth()` using formula = 'y ~ x'
# Visualize most complex interaction (just for fun)
# g4 <- ggplot(data_long_50, aes(x=Reliance, y=Trust, color=Reliability_factor, group=Reliability_factor)) +
# geom_smooth(alpha = 0.1, method = 'lm') +
# geom_point() +
# theme_classic() +
# labs(title = "Trust by Reliance by Reliability", x = "Reliance", y = "Trust") +
# theme(plot.title = element_text(size=title_size)) +
# facet_wrap(~Condition * Reliability_factor) +
# xlim(0, 1) +
# ylim(0, 100)
# print(g4)
flexplot(data = data_long_50, Trust ~ Reliance + Reliability_factor | Condition + Confidence, method = 'lm')
# Everything Model
m50_2 <- lmer(data = data_long_50, Reliance ~ Condition * Reliability * Confidence * Trust * (1 | Participant))
## Warning: Some predictor variables are on very different scales: consider
## rescaling
summary(m50_2)
## Linear mixed model fit by REML ['lmerMod']
## Formula: Reliance ~ Condition * Reliability * Confidence * Trust * (1 |
## Participant)
## Data: data_long_50
##
## REML criterion at convergence: -16.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9338 -0.4904 -0.0450 0.4329 4.1183
##
## Random effects:
## Groups Name Variance Std.Dev.
## Participant (Intercept) 0.10096 0.3177
## Residual 0.02064 0.1437
## Number of obs: 480, groups: Participant, 80
##
## Fixed effects:
## Estimate Std. Error
## (Intercept) -3.904e+00 1.644e+00
## Condition50% Increasing 5.890e+00 2.237e+00
## Reliability 6.131e-02 2.057e-02
## Confidence 4.138e-02 1.842e-02
## Trust 5.605e-02 2.440e-02
## Condition50% Increasing:Reliability -7.959e-02 2.697e-02
## Condition50% Increasing:Confidence -5.273e-02 2.646e-02
## Reliability:Confidence -6.265e-04 2.330e-04
## Condition50% Increasing:Trust -8.274e-02 3.218e-02
## Reliability:Trust -7.470e-04 2.976e-04
## Confidence:Trust -5.697e-04 2.598e-04
## Condition50% Increasing:Reliability:Confidence 7.024e-04 3.198e-04
## Condition50% Increasing:Reliability:Trust 1.016e-03 3.868e-04
## Condition50% Increasing:Confidence:Trust 7.625e-04 3.544e-04
## Reliability:Confidence:Trust 7.822e-06 3.200e-06
## Condition50% Increasing:Reliability:Confidence:Trust -8.944e-06 4.255e-06
## t value
## (Intercept) -2.374
## Condition50% Increasing 2.632
## Reliability 2.980
## Confidence 2.247
## Trust 2.298
## Condition50% Increasing:Reliability -2.951
## Condition50% Increasing:Confidence -1.993
## Reliability:Confidence -2.688
## Condition50% Increasing:Trust -2.571
## Reliability:Trust -2.510
## Confidence:Trust -2.192
## Condition50% Increasing:Reliability:Confidence 2.196
## Condition50% Increasing:Reliability:Trust 2.626
## Condition50% Increasing:Confidence:Trust 2.151
## Reliability:Confidence:Trust 2.445
## Condition50% Increasing:Reliability:Confidence:Trust -2.102
##
## Correlation matrix not shown by default, as p = 16 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling
tab_model(m50_2)
| Â | Reliance | ||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | -3.90 | -7.14 – -0.67 | 0.018 |
|
Condition [50% Increasing] |
5.89 | 1.49 – 10.29 | 0.009 |
| Reliability | 0.06 | 0.02 – 0.10 | 0.003 |
| Confidence | 0.04 | 0.01 – 0.08 | 0.025 |
| Trust | 0.06 | 0.01 – 0.10 | 0.022 |
|
Condition [50% Increasing] × Reliability |
-0.08 | -0.13 – -0.03 | 0.003 |
|
Condition [50% Increasing] × Confidence |
-0.05 | -0.10 – -0.00 | 0.047 |
| Reliability × Confidence | -0.00 | -0.00 – -0.00 | 0.007 |
|
Condition [50% Increasing] × Trust |
-0.08 | -0.15 – -0.02 | 0.010 |
| Reliability × Trust | -0.00 | -0.00 – -0.00 | 0.012 |
| Confidence × Trust | -0.00 | -0.00 – -0.00 | 0.029 |
|
(Condition [50% Increasing] × Reliability) × Confidence |
0.00 | 0.00 – 0.00 | 0.029 |
|
(Condition [50% Increasing] × Reliability) × Trust |
0.00 | 0.00 – 0.00 | 0.009 |
|
(Condition [50% Increasing] × Confidence) × Trust |
0.00 | 0.00 – 0.00 | 0.032 |
|
(Reliability × Confidence) × Trust |
0.00 | 0.00 – 0.00 | 0.015 |
|
(Condition [50% Increasing] × Reliability × Confidence) × Trust |
-0.00 | -0.00 – -0.00 | 0.036 |
| Random Effects | |||
| σ2 | 0.02 | ||
| τ00 Participant | 0.10 | ||
| ICC | 0.83 | ||
| N Participant | 80 | ||
| Observations | 480 | ||
| Marginal R2 / Conditional R2 | 0.046 / 0.838 | ||
# Visualize Dependence by Trust
g1 <- ggplot(data_long_50, aes(x=Trust, y=Reliance)) +
geom_smooth(alpha = 0.5, method = 'lm') +
geom_point() +
theme_classic() +
labs(title = "Dependence by Trust", x = "Trust", y = "Dependence") +
theme(plot.title = element_text(size=title_size)) +
xlim(0, 100) +
ylim(0, 1)
print(g1)
## `geom_smooth()` using formula = 'y ~ x'
# Visualize Dependence by Trust and Condition
g2 <- ggplot(data_long_50, aes(x=Trust, y=Reliance, color=Condition)) +
geom_smooth(alpha = 0.5, method = 'lm') +
geom_point() +
theme_classic() +
labs(title = "Dependence by Trust by Condition", x = "Trust", y = "Dependence") +
theme(plot.title = element_text(size=title_size)) +
xlim(0, 100) +
ylim(0, 1)
print(g2)
## `geom_smooth()` using formula = 'y ~ x'
# Visualize Dependence by Trust and Reliability
g3 <- ggplot(data_long_50, aes(x=Trust, y=Reliance, color=Reliability_factor, group=Reliability_factor)) +
geom_smooth(alpha = 0.1, method = 'lm') +
geom_point() +
theme_classic() +
labs(title = "Dependence by Trust by Reliability", x = "Trust", y = "Dependence") +
theme(plot.title = element_text(size=title_size)) +
facet_wrap(~Condition) +
xlim(0, 100) +
ylim(0, 1)
print(g3)
## `geom_smooth()` using formula = 'y ~ x'
# Remove Reliability and add Confidence
flexplot(data = data_long_50, Reliance ~ Trust + Confidence | Condition, method = 'lm', se = TRUE)
# Visualize most complex interaction
flexplot(data = data_long_50, Reliance ~ Trust + Reliability_factor | Condition + Confidence, method = 'lm')
# Everything Model
m50_3 <- lmer(data = data_long_50, Performance_After ~ Condition * Reliability * Confidence * Trust * Reliance * (1 | Participant))
## Warning: Some predictor variables are on very different scales: consider
## rescaling
summary(m50_3)
## Linear mixed model fit by REML ['lmerMod']
## Formula: Performance_After ~ Condition * Reliability * Confidence * Trust *
## Reliance * (1 | Participant)
## Data: data_long_50
##
## REML criterion at convergence: -584.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.4197 -0.5144 -0.0200 0.5663 2.6916
##
## Random effects:
## Groups Name Variance Std.Dev.
## Participant (Intercept) 0.011427 0.10690
## Residual 0.004294 0.06553
## Number of obs: 480, groups: Participant, 80
##
## Fixed effects:
## Estimate
## (Intercept) 2.391e+00
## Condition50% Increasing -9.952e-01
## Reliability -1.678e-02
## Confidence -1.368e-02
## Trust -2.810e-02
## Reliance -2.773e-01
## Condition50% Increasing:Reliability 1.135e-02
## Condition50% Increasing:Confidence -1.461e-03
## Reliability:Confidence 1.151e-04
## Condition50% Increasing:Trust 1.186e-02
## Reliability:Trust 2.852e-04
## Confidence:Trust 2.638e-04
## Condition50% Increasing:Reliance -1.122e+00
## Reliability:Reliance 1.570e-02
## Confidence:Reliance -1.742e-02
## Trust:Reliance 2.089e-02
## Condition50% Increasing:Reliability:Confidence 3.644e-05
## Condition50% Increasing:Reliability:Trust -2.043e-04
## Condition50% Increasing:Confidence:Trust 8.118e-06
## Reliability:Confidence:Trust -2.370e-06
## Condition50% Increasing:Reliability:Reliance -1.965e-03
## Condition50% Increasing:Confidence:Reliance 4.439e-02
## Reliability:Confidence:Reliance 6.345e-05
## Condition50% Increasing:Trust:Reliance 6.590e-03
## Reliability:Trust:Reliance -3.542e-04
## Confidence:Trust:Reliance -9.137e-05
## Condition50% Increasing:Reliability:Confidence:Trust 4.747e-07
## Condition50% Increasing:Reliability:Confidence:Reliance -3.679e-04
## Condition50% Increasing:Reliability:Trust:Reliance 1.540e-04
## Condition50% Increasing:Confidence:Trust:Reliance -4.235e-04
## Reliability:Confidence:Trust:Reliance 2.351e-06
## Condition50% Increasing:Reliability:Confidence:Trust:Reliance 2.524e-06
## Std. Error
## (Intercept) 1.190e+00
## Condition50% Increasing 1.608e+00
## Reliability 1.673e-02
## Confidence 1.300e-02
## Trust 1.680e-02
## Reliance 3.558e+00
## Condition50% Increasing:Reliability 2.070e-02
## Condition50% Increasing:Confidence 1.835e-02
## Reliability:Confidence 1.848e-04
## Condition50% Increasing:Trust 2.284e-02
## Reliability:Trust 2.285e-04
## Confidence:Trust 1.775e-04
## Condition50% Increasing:Reliance 4.542e+00
## Reliability:Reliance 4.478e-02
## Confidence:Reliance 3.996e-02
## Trust:Reliance 4.760e-02
## Condition50% Increasing:Reliability:Confidence 2.332e-04
## Condition50% Increasing:Reliability:Trust 2.928e-04
## Condition50% Increasing:Confidence:Trust 2.463e-04
## Reliability:Confidence:Trust 2.446e-06
## Condition50% Increasing:Reliability:Reliance 5.632e-02
## Condition50% Increasing:Confidence:Reliance 5.386e-02
## Reliability:Confidence:Reliance 5.041e-04
## Condition50% Increasing:Trust:Reliance 5.918e-02
## Reliability:Trust:Reliance 5.978e-04
## Confidence:Trust:Reliance 5.106e-04
## Condition50% Increasing:Reliability:Confidence:Trust 3.127e-06
## Condition50% Increasing:Reliability:Confidence:Reliance 6.695e-04
## Condition50% Increasing:Reliability:Trust:Reliance 7.323e-04
## Condition50% Increasing:Confidence:Trust:Reliance 6.571e-04
## Reliability:Confidence:Trust:Reliance 6.457e-06
## Condition50% Increasing:Reliability:Confidence:Trust:Reliance 8.173e-06
## t value
## (Intercept) 2.009
## Condition50% Increasing -0.619
## Reliability -1.003
## Confidence -1.052
## Trust -1.672
## Reliance -0.078
## Condition50% Increasing:Reliability 0.548
## Condition50% Increasing:Confidence -0.080
## Reliability:Confidence 0.623
## Condition50% Increasing:Trust 0.519
## Reliability:Trust 1.248
## Confidence:Trust 1.486
## Condition50% Increasing:Reliance -0.247
## Reliability:Reliance 0.351
## Confidence:Reliance -0.436
## Trust:Reliance 0.439
## Condition50% Increasing:Reliability:Confidence 0.156
## Condition50% Increasing:Reliability:Trust -0.698
## Condition50% Increasing:Confidence:Trust 0.033
## Reliability:Confidence:Trust -0.969
## Condition50% Increasing:Reliability:Reliance -0.035
## Condition50% Increasing:Confidence:Reliance 0.824
## Reliability:Confidence:Reliance 0.126
## Condition50% Increasing:Trust:Reliance 0.111
## Reliability:Trust:Reliance -0.593
## Confidence:Trust:Reliance -0.179
## Condition50% Increasing:Reliability:Confidence:Trust 0.152
## Condition50% Increasing:Reliability:Confidence:Reliance -0.550
## Condition50% Increasing:Reliability:Trust:Reliance 0.210
## Condition50% Increasing:Confidence:Trust:Reliance -0.644
## Reliability:Confidence:Trust:Reliance 0.364
## Condition50% Increasing:Reliability:Confidence:Trust:Reliance 0.309
##
## Correlation matrix not shown by default, as p = 32 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling
tab_model(m50_3)
| Â | Performance After | ||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 2.39 | 0.05 – 4.73 | 0.045 |
|
Condition [50% Increasing] |
-1.00 | -4.16 – 2.16 | 0.536 |
| Reliability | -0.02 | -0.05 – 0.02 | 0.317 |
| Confidence | -0.01 | -0.04 – 0.01 | 0.293 |
| Trust | -0.03 | -0.06 – 0.00 | 0.095 |
| Reliance | -0.28 | -7.27 – 6.72 | 0.938 |
|
Condition [50% Increasing] × Reliability |
0.01 | -0.03 – 0.05 | 0.584 |
|
Condition [50% Increasing] × Confidence |
-0.00 | -0.04 – 0.03 | 0.937 |
| Reliability × Confidence | 0.00 | -0.00 – 0.00 | 0.534 |
|
Condition [50% Increasing] × Trust |
0.01 | -0.03 – 0.06 | 0.604 |
| Reliability × Trust | 0.00 | -0.00 – 0.00 | 0.213 |
| Confidence × Trust | 0.00 | -0.00 – 0.00 | 0.138 |
|
Condition [50% Increasing] × Reliance |
-1.12 | -10.05 – 7.80 | 0.805 |
| Reliability × Reliance | 0.02 | -0.07 – 0.10 | 0.726 |
| Confidence × Reliance | -0.02 | -0.10 – 0.06 | 0.663 |
| Trust × Reliance | 0.02 | -0.07 – 0.11 | 0.661 |
|
(Condition [50% Increasing] × Reliability) × Confidence |
0.00 | -0.00 – 0.00 | 0.876 |
|
(Condition [50% Increasing] × Reliability) × Trust |
-0.00 | -0.00 – 0.00 | 0.486 |
|
(Condition [50% Increasing] × Confidence) × Trust |
0.00 | -0.00 – 0.00 | 0.974 |
|
(Reliability × Confidence) × Trust |
-0.00 | -0.00 – 0.00 | 0.333 |
|
(Condition [50% Increasing] × Reliability) × Reliance |
-0.00 | -0.11 – 0.11 | 0.972 |
|
(Condition [50% Increasing] × Confidence) × Reliance |
0.04 | -0.06 – 0.15 | 0.410 |
|
(Reliability × Confidence) × Reliance |
0.00 | -0.00 – 0.00 | 0.900 |
|
(Condition [50% Increasing] × Trust) × Reliance |
0.01 | -0.11 – 0.12 | 0.911 |
|
(Reliability × Trust) × Reliance |
-0.00 | -0.00 – 0.00 | 0.554 |
|
(Confidence × Trust) × Reliance |
-0.00 | -0.00 – 0.00 | 0.858 |
|
(Condition [50% Increasing] × Reliability × Confidence) × Trust |
0.00 | -0.00 – 0.00 | 0.879 |
|
(Condition [50% Increasing] × Reliability × Confidence) × Reliance |
-0.00 | -0.00 – 0.00 | 0.583 |
|
(Condition [50% Increasing] × Reliability × Trust) × Reliance |
0.00 | -0.00 – 0.00 | 0.833 |
|
(Condition [50% Increasing] × Confidence × Trust) × Reliance |
-0.00 | -0.00 – 0.00 | 0.520 |
|
(Reliability × Confidence × Trust) × Reliance |
0.00 | -0.00 – 0.00 | 0.716 |
|
(Condition [50% Increasing] × Reliability × Confidence × Trust) × Reliance |
0.00 | -0.00 – 0.00 | 0.758 |
| Random Effects | |||
| σ2 | 0.00 | ||
| τ00 Participant | 0.01 | ||
| ICC | 0.73 | ||
| N Participant | 80 | ||
| Observations | 480 | ||
| Marginal R2 / Conditional R2 | 0.334 / 0.818 | ||
# trust by performance
g1 <- ggplot(data_long_50, aes(x=Trust, y=Performance_After)) +
geom_smooth(alpha = 0.5, method = 'lm') +
geom_point() +
theme_classic() +
labs(title = "Performance After by Trust by Condition", x = "Trust", y = "Performance After") +
theme(plot.title = element_text(size=title_size)) +
xlim(0, 100) +
ylim(0, 1)
print(g1)
## `geom_smooth()` using formula = 'y ~ x'
# Everything Model
m70_1 <- lmer(data = data_long_70, Trust ~ Condition * Reliability * Confidence * Reliance * (1 | Participant))
## Warning: Some predictor variables are on very different scales: consider
## rescaling
summary(m70_1)
## Linear mixed model fit by REML ['lmerMod']
## Formula: Trust ~ Condition * Reliability * Confidence * Reliance * (1 |
## Participant)
## Data: data_long_70
##
## REML criterion at convergence: 3147.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.1663 -0.4908 0.0266 0.5266 4.5948
##
## Random effects:
## Groups Name Variance Std.Dev.
## Participant (Intercept) 78.09 8.837
## Residual 20.66 4.546
## Number of obs: 486, groups: Participant, 81
##
## Fixed effects:
## Estimate Std. Error
## (Intercept) 50.543933 27.169845
## Condition70% Increasing -21.852125 34.026793
## Reliability -0.348433 0.324246
## Confidence 0.222184 0.312859
## Reliance -94.298837 59.674490
## Condition70% Increasing:Reliability 0.349005 0.393641
## Condition70% Increasing:Confidence 0.334764 0.395000
## Reliability:Confidence 0.005676 0.003745
## Condition70% Increasing:Reliance 155.216558 72.193542
## Reliability:Reliance 1.223567 0.698786
## Confidence:Reliance 1.331890 0.679141
## Condition70% Increasing:Reliability:Confidence -0.005288 0.004567
## Condition70% Increasing:Reliability:Reliance -1.708054 0.826693
## Condition70% Increasing:Confidence:Reliance -1.981159 0.833851
## Reliability:Confidence:Reliance -0.016796 0.007905
## Condition70% Increasing:Reliability:Confidence:Reliance 0.022030 0.009494
## t value
## (Intercept) 1.860
## Condition70% Increasing -0.642
## Reliability -1.075
## Confidence 0.710
## Reliance -1.580
## Condition70% Increasing:Reliability 0.887
## Condition70% Increasing:Confidence 0.848
## Reliability:Confidence 1.516
## Condition70% Increasing:Reliance 2.150
## Reliability:Reliance 1.751
## Confidence:Reliance 1.961
## Condition70% Increasing:Reliability:Confidence -1.158
## Condition70% Increasing:Reliability:Reliance -2.066
## Condition70% Increasing:Confidence:Reliance -2.376
## Reliability:Confidence:Reliance -2.125
## Condition70% Increasing:Reliability:Confidence:Reliance 2.320
##
## Correlation matrix not shown by default, as p = 16 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling
tab_model(m70_1)
| Â | Trust | ||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 50.54 | -2.85 – 103.93 | 0.063 |
|
Condition [70% Increasing] |
-21.85 | -88.72 – 45.01 | 0.521 |
| Reliability | -0.35 | -0.99 – 0.29 | 0.283 |
| Confidence | 0.22 | -0.39 – 0.84 | 0.478 |
| Reliance | -94.30 | -211.56 – 22.96 | 0.115 |
|
Condition [70% Increasing] × Reliability |
0.35 | -0.42 – 1.12 | 0.376 |
|
Condition [70% Increasing] × Confidence |
0.33 | -0.44 – 1.11 | 0.397 |
| Reliability × Confidence | 0.01 | -0.00 – 0.01 | 0.130 |
|
Condition [70% Increasing] × Reliance |
155.22 | 13.35 – 297.08 | 0.032 |
| Reliability × Reliance | 1.22 | -0.15 – 2.60 | 0.081 |
| Confidence × Reliance | 1.33 | -0.00 – 2.67 | 0.050 |
|
(Condition [70% Increasing] × Reliability) × Confidence |
-0.01 | -0.01 – 0.00 | 0.247 |
|
(Condition [70% Increasing] × Reliability) × Reliance |
-1.71 | -3.33 – -0.08 | 0.039 |
|
(Condition [70% Increasing] × Confidence) × Reliance |
-1.98 | -3.62 – -0.34 | 0.018 |
|
(Reliability × Confidence) × Reliance |
-0.02 | -0.03 – -0.00 | 0.034 |
|
(Condition [70% Increasing] × Reliability × Confidence) × Reliance |
0.02 | 0.00 – 0.04 | 0.021 |
| Random Effects | |||
| σ2 | 20.66 | ||
| τ00 Participant | 78.09 | ||
| ICC | 0.79 | ||
| N Participant | 81 | ||
| Observations | 486 | ||
| Marginal R2 / Conditional R2 | 0.400 / 0.874 | ||
# Visualize Condition by reliance
g1 <- ggplot(data_long_70, aes(x=Reliance, y=Trust, color=Condition)) +
geom_smooth(alpha = 0.5, method = 'lm') +
geom_point() +
theme_classic() +
labs(title = "Trust by Reliance by Condition", x = "Reliance", y = "Trust") +
theme(plot.title = element_text(size=title_size)) +
xlim(0, 1) +
ylim(0, 100)
print(g1)
## `geom_smooth()` using formula = 'y ~ x'
# Condition bu Reliability by Reliance
g2 <- ggplot(data_long_70, aes(x=Reliance, y=Trust, color=Reliability_factor, group=Reliability_factor)) +
geom_smooth(alpha = 0.1, method = 'lm') +
geom_point() +
theme_classic() +
labs(title = "Trust by Reliance by Reliability", x = "Reliance", y = "Trust") +
theme(plot.title = element_text(size=title_size)) +
facet_wrap(~Condition) +
xlim(0, 1) +
ylim(0, 100)
print(g2)
## `geom_smooth()` using formula = 'y ~ x'
# Condition by Reliability by Reliance by Confidence
flexplot(data = data_long_70, Trust ~ Reliance + Reliability_factor | Condition + Confidence, method = 'lm')
# Everything Model
m70_2 <- lmer(data = data_long_70, Reliance ~ Condition * Reliability * Confidence * Trust * (1 | Participant))
## Warning: Some predictor variables are on very different scales: consider
## rescaling
summary(m70_2)
## Linear mixed model fit by REML ['lmerMod']
## Formula: Reliance ~ Condition * Reliability * Confidence * Trust * (1 |
## Participant)
## Data: data_long_70
##
## REML criterion at convergence: 52
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0740 -0.4960 -0.0191 0.5240 3.3555
##
## Random effects:
## Groups Name Variance Std.Dev.
## Participant (Intercept) 0.09502 0.3082
## Residual 0.02520 0.1587
## Number of obs: 486, groups: Participant, 81
##
## Fixed effects:
## Estimate Std. Error
## (Intercept) -6.846e-01 2.560e+00
## Condition70% Increasing -1.410e+00 3.418e+00
## Reliability 7.159e-03 3.085e-02
## Confidence 1.333e-02 3.395e-02
## Trust 3.118e-02 3.409e-02
## Condition70% Increasing:Reliability 1.396e-02 4.024e-02
## Condition70% Increasing:Confidence 2.361e-02 4.460e-02
## Reliability:Confidence -1.030e-04 4.116e-04
## Condition70% Increasing:Trust -2.484e-03 4.640e-02
## Reliability:Trust -3.072e-04 4.036e-04
## Confidence:Trust -3.859e-04 4.168e-04
## Condition70% Increasing:Reliability:Confidence -2.650e-04 5.250e-04
## Condition70% Increasing:Reliability:Trust 1.161e-04 5.418e-04
## Condition70% Increasing:Confidence:Trust -4.936e-05 5.638e-04
## Reliability:Confidence:Trust 4.127e-06 4.980e-06
## Condition70% Increasing:Reliability:Confidence:Trust -3.638e-07 6.583e-06
## t value
## (Intercept) -0.267
## Condition70% Increasing -0.413
## Reliability 0.232
## Confidence 0.393
## Trust 0.914
## Condition70% Increasing:Reliability 0.347
## Condition70% Increasing:Confidence 0.529
## Reliability:Confidence -0.250
## Condition70% Increasing:Trust -0.054
## Reliability:Trust -0.761
## Confidence:Trust -0.926
## Condition70% Increasing:Reliability:Confidence -0.505
## Condition70% Increasing:Reliability:Trust 0.214
## Condition70% Increasing:Confidence:Trust -0.088
## Reliability:Confidence:Trust 0.829
## Condition70% Increasing:Reliability:Confidence:Trust -0.055
##
## Correlation matrix not shown by default, as p = 16 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling
tab_model(m70_2)
| Â | Reliance | ||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | -0.68 | -5.72 – 4.35 | 0.789 |
|
Condition [70% Increasing] |
-1.41 | -8.13 – 5.31 | 0.680 |
| Reliability | 0.01 | -0.05 – 0.07 | 0.817 |
| Confidence | 0.01 | -0.05 – 0.08 | 0.695 |
| Trust | 0.03 | -0.04 – 0.10 | 0.361 |
|
Condition [70% Increasing] × Reliability |
0.01 | -0.07 – 0.09 | 0.729 |
|
Condition [70% Increasing] × Confidence |
0.02 | -0.06 – 0.11 | 0.597 |
| Reliability × Confidence | -0.00 | -0.00 – 0.00 | 0.802 |
|
Condition [70% Increasing] × Trust |
-0.00 | -0.09 – 0.09 | 0.957 |
| Reliability × Trust | -0.00 | -0.00 – 0.00 | 0.447 |
| Confidence × Trust | -0.00 | -0.00 – 0.00 | 0.355 |
|
(Condition [70% Increasing] × Reliability) × Confidence |
-0.00 | -0.00 – 0.00 | 0.614 |
|
(Condition [70% Increasing] × Reliability) × Trust |
0.00 | -0.00 – 0.00 | 0.830 |
|
(Condition [70% Increasing] × Confidence) × Trust |
-0.00 | -0.00 – 0.00 | 0.930 |
|
(Reliability × Confidence) × Trust |
0.00 | -0.00 – 0.00 | 0.408 |
|
(Condition [70% Increasing] × Reliability × Confidence) × Trust |
-0.00 | -0.00 – 0.00 | 0.956 |
| Random Effects | |||
| σ2 | 0.03 | ||
| τ00 Participant | 0.10 | ||
| ICC | 0.79 | ||
| N Participant | 81 | ||
| Observations | 486 | ||
| Marginal R2 / Conditional R2 | 0.035 / 0.798 | ||
Aparently othing in the model matters…. so no visuals
# Everything Model
m70_3 <- lmer(data = data_long_70, Performance_After ~ Condition * Reliability * Confidence * Trust * Reliance * (1 | Participant))
## Warning: Some predictor variables are on very different scales: consider
## rescaling
summary(m70_3)
## Linear mixed model fit by REML ['lmerMod']
## Formula: Performance_After ~ Condition * Reliability * Confidence * Trust *
## Reliance * (1 | Participant)
## Data: data_long_70
##
## REML criterion at convergence: -707.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.2430 -0.4611 0.0343 0.5755 2.7041
##
## Random effects:
## Groups Name Variance Std.Dev.
## Participant (Intercept) 0.006763 0.08224
## Residual 0.003617 0.06014
## Number of obs: 486, groups: Participant, 81
##
## Fixed effects:
## Estimate
## (Intercept) -1.872e+00
## Condition70% Increasing 5.126e+00
## Reliability 2.960e-02
## Confidence 4.062e-02
## Trust 2.489e-02
## Reliance 3.808e+00
## Condition70% Increasing:Reliability -5.661e-02
## Condition70% Increasing:Confidence -7.029e-02
## Reliability:Confidence -4.254e-04
## Condition70% Increasing:Trust -5.955e-02
## Reliability:Trust -3.704e-04
## Confidence:Trust -3.922e-04
## Condition70% Increasing:Reliance -6.733e+00
## Reliability:Reliance -5.343e-02
## Confidence:Reliance -6.733e-02
## Trust:Reliance -4.612e-02
## Condition70% Increasing:Reliability:Confidence 7.257e-04
## Condition70% Increasing:Reliability:Trust 7.681e-04
## Condition70% Increasing:Confidence:Trust 7.991e-04
## Reliability:Confidence:Trust 5.083e-06
## Condition70% Increasing:Reliability:Reliance 8.649e-02
## Condition70% Increasing:Confidence:Reliance 7.250e-02
## Reliability:Confidence:Reliance 8.483e-04
## Condition70% Increasing:Trust:Reliance 6.773e-02
## Reliability:Trust:Reliance 8.039e-04
## Confidence:Trust:Reliance 6.924e-04
## Condition70% Increasing:Reliability:Confidence:Trust -9.443e-06
## Condition70% Increasing:Reliability:Confidence:Reliance -8.890e-04
## Condition70% Increasing:Reliability:Trust:Reliance -1.110e-03
## Condition70% Increasing:Confidence:Trust:Reliance -6.727e-04
## Reliability:Confidence:Trust:Reliance -1.054e-05
## Condition70% Increasing:Reliability:Confidence:Trust:Reliance 1.096e-05
## Std. Error
## (Intercept) 2.074e+00
## Condition70% Increasing 2.554e+00
## Reliability 2.533e-02
## Confidence 2.577e-02
## Trust 2.631e-02
## Reliance 4.606e+00
## Condition70% Increasing:Reliability 3.013e-02
## Condition70% Increasing:Confidence 3.111e-02
## Reliability:Confidence 3.180e-04
## Condition70% Increasing:Trust 3.499e-02
## Reliability:Trust 3.188e-04
## Confidence:Trust 3.091e-04
## Condition70% Increasing:Reliance 6.785e+00
## Reliability:Reliance 5.550e-02
## Confidence:Reliance 5.501e-02
## Trust:Reliance 5.792e-02
## Condition70% Increasing:Reliability:Confidence 3.706e-04
## Condition70% Increasing:Reliability:Trust 4.055e-04
## Condition70% Increasing:Confidence:Trust 4.006e-04
## Reliability:Confidence:Trust 3.777e-06
## Condition70% Increasing:Reliability:Reliance 7.773e-02
## Condition70% Increasing:Confidence:Reliance 8.052e-02
## Reliability:Confidence:Reliance 6.627e-04
## Condition70% Increasing:Trust:Reliance 8.632e-02
## Reliability:Trust:Reliance 6.974e-04
## Confidence:Trust:Reliance 6.640e-04
## Condition70% Increasing:Reliability:Confidence:Trust 4.676e-06
## Condition70% Increasing:Reliability:Confidence:Reliance 9.234e-04
## Condition70% Increasing:Reliability:Trust:Reliance 9.870e-04
## Condition70% Increasing:Confidence:Trust:Reliance 9.970e-04
## Reliability:Confidence:Trust:Reliance 7.993e-06
## Condition70% Increasing:Reliability:Confidence:Trust:Reliance 1.140e-05
## t value
## (Intercept) -0.902
## Condition70% Increasing 2.007
## Reliability 1.169
## Confidence 1.576
## Trust 0.946
## Reliance 0.827
## Condition70% Increasing:Reliability -1.879
## Condition70% Increasing:Confidence -2.259
## Reliability:Confidence -1.338
## Condition70% Increasing:Trust -1.702
## Reliability:Trust -1.162
## Confidence:Trust -1.269
## Condition70% Increasing:Reliance -0.992
## Reliability:Reliance -0.963
## Confidence:Reliance -1.224
## Trust:Reliance -0.796
## Condition70% Increasing:Reliability:Confidence 1.958
## Condition70% Increasing:Reliability:Trust 1.894
## Condition70% Increasing:Confidence:Trust 1.995
## Reliability:Confidence:Trust 1.346
## Condition70% Increasing:Reliability:Reliance 1.113
## Condition70% Increasing:Confidence:Reliance 0.900
## Reliability:Confidence:Reliance 1.280
## Condition70% Increasing:Trust:Reliance 0.785
## Reliability:Trust:Reliance 1.153
## Confidence:Trust:Reliance 1.043
## Condition70% Increasing:Reliability:Confidence:Trust -2.019
## Condition70% Increasing:Reliability:Confidence:Reliance -0.963
## Condition70% Increasing:Reliability:Trust:Reliance -1.124
## Condition70% Increasing:Confidence:Trust:Reliance -0.675
## Reliability:Confidence:Trust:Reliance -1.318
## Condition70% Increasing:Reliability:Confidence:Trust:Reliance 0.962
##
## Correlation matrix not shown by default, as p = 32 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling
tab_model(m70_3)
| Â | Performance After | ||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | -1.87 | -5.95 – 2.20 | 0.367 |
|
Condition [70% Increasing] |
5.13 | 0.11 – 10.15 | 0.045 |
| Reliability | 0.03 | -0.02 – 0.08 | 0.243 |
| Confidence | 0.04 | -0.01 – 0.09 | 0.116 |
| Trust | 0.02 | -0.03 – 0.08 | 0.345 |
| Reliance | 3.81 | -5.24 – 12.86 | 0.409 |
|
Condition [70% Increasing] × Reliability |
-0.06 | -0.12 – 0.00 | 0.061 |
|
Condition [70% Increasing] × Confidence |
-0.07 | -0.13 – -0.01 | 0.024 |
| Reliability × Confidence | -0.00 | -0.00 – 0.00 | 0.182 |
|
Condition [70% Increasing] × Trust |
-0.06 | -0.13 – 0.01 | 0.089 |
| Reliability × Trust | -0.00 | -0.00 – 0.00 | 0.246 |
| Confidence × Trust | -0.00 | -0.00 – 0.00 | 0.205 |
|
Condition [70% Increasing] × Reliance |
-6.73 | -20.07 – 6.60 | 0.322 |
| Reliability × Reliance | -0.05 | -0.16 – 0.06 | 0.336 |
| Confidence × Reliance | -0.07 | -0.18 – 0.04 | 0.222 |
| Trust × Reliance | -0.05 | -0.16 – 0.07 | 0.426 |
|
(Condition [70% Increasing] × Reliability) × Confidence |
0.00 | -0.00 – 0.00 | 0.051 |
|
(Condition [70% Increasing] × Reliability) × Trust |
0.00 | -0.00 – 0.00 | 0.059 |
|
(Condition [70% Increasing] × Confidence) × Trust |
0.00 | 0.00 – 0.00 | 0.047 |
|
(Reliability × Confidence) × Trust |
0.00 | -0.00 – 0.00 | 0.179 |
|
(Condition [70% Increasing] × Reliability) × Reliance |
0.09 | -0.07 – 0.24 | 0.266 |
|
(Condition [70% Increasing] × Confidence) × Reliance |
0.07 | -0.09 – 0.23 | 0.368 |
|
(Reliability × Confidence) × Reliance |
0.00 | -0.00 – 0.00 | 0.201 |
|
(Condition [70% Increasing] × Trust) × Reliance |
0.07 | -0.10 – 0.24 | 0.433 |
|
(Reliability × Trust) × Reliance |
0.00 | -0.00 – 0.00 | 0.250 |
|
(Confidence × Trust) × Reliance |
0.00 | -0.00 – 0.00 | 0.298 |
|
(Condition [70% Increasing] × Reliability × Confidence) × Trust |
-0.00 | -0.00 – -0.00 | 0.044 |
|
(Condition [70% Increasing] × Reliability × Confidence) × Reliance |
-0.00 | -0.00 – 0.00 | 0.336 |
|
(Condition [70% Increasing] × Reliability × Trust) × Reliance |
-0.00 | -0.00 – 0.00 | 0.262 |
|
(Condition [70% Increasing] × Confidence × Trust) × Reliance |
-0.00 | -0.00 – 0.00 | 0.500 |
|
(Reliability × Confidence × Trust) × Reliance |
-0.00 | -0.00 – 0.00 | 0.188 |
|
(Condition [70% Increasing] × Reliability × Confidence × Trust) × Reliance |
0.00 | -0.00 – 0.00 | 0.337 |
| Random Effects | |||
| σ2 | 0.00 | ||
| τ00 Participant | 0.01 | ||
| ICC | 0.65 | ||
| N Participant | 81 | ||
| Observations | 486 | ||
| Marginal R2 / Conditional R2 | 0.375 / 0.782 | ||
# performance by condition
# g1 <- ggplot(data_long_70, aes(x=Condition_num, y=Performance_After)) +
# geom_smooth(mehtod='lm') +
# geom_beeswarm() +
# theme_classic() +
# theme(plot.title = element_text(size=title_size)) +
# ylim(0, 1)
# print(g1)
flexplot(data = data_long_70, Performance_After ~ Condition, method = 'lm')
# Condition by Confidence
flexplot(data = data_long_70, Performance_After ~ Condition + Confidence, method = 'lm')
g2 <- ggplot(data_long_70, aes(x=Confidence, y=Performance_After, color=Condition)) +
geom_smooth(alpha = 0.5, method = 'lm') +
geom_point() +
theme_classic() +
labs(title = "Performance After by Confidence by Condition", x = "Confidence", y = "Performance After") +
theme(plot.title = element_text(size=title_size)) +
xlim(0, 100) +
ylim(0, 1)
print(g2)
## `geom_smooth()` using formula = 'y ~ x'
# Condition by Confidence by Trust
flexplot(data = data_long_70, Performance_After ~ Confidence + Trust | Condition, method = 'lm')
flexplot(data = data_long_70, Performance_After ~ Trust + Condition | Confidence, method = 'lm')
# Condition by Reliability, by Confidence, by Trust
flexplot(data = data_long_70, Performance_After ~ Trust + Confidence | Condition + Reliability_factor, method = 'lm')